Diving Beneath the Sea of Stellar Activity: Chromatic Radial Velocities of the Young AU Mic Planetary System
Bibliographic record
Abstract
Abstract We present updated radial-velocity (RV) analyses of the AU Mic system. AU Mic is a young (22 Myr) early-M dwarf known to host two transiting planets—P b ∼ 8.46 days, R b = 4.38 − 0.18 + 0.18 R ⊕ , P c ∼ 18.86 days, R c = 3.51 − 0.16 + 0.16 R ⊕ . With visible RVs from Calar Alto high-Resolution search for M dwarfs with Exo-earths with Near-infrared and optical echelle Spectrographs (CARMENES)-VIS, CHIRON, HARPS, HIRES, Minerva-Australis, and Tillinghast Reflector Echelle Spectrograph, as well as near-infrared (NIR) RVs from CARMENES-NIR, CSHELL, IRD, iSHELL, NIRSPEC, and SPIRou, we provide a 5σ upper limit to the mass of AU Mic c of M c ≤ 20.13 M ⊕ and present a refined mass of AU Mic b of M b = 20.12 − 1.57 + 1.72 M ⊕ . Used in our analyses is a new RV modeling toolkit to exploit the wavelength dependence of stellar activity present in our RVs via wavelength-dependent Gaussian processes. By obtaining near-simultaneous visible and near-infrared RVs, we also compute the temporal evolution of RV “color” and introduce a regressional method to aid in isolating Keplerian from stellar activity signals when modeling RVs in future works. Using a multiwavelength Gaussian process model, we demonstrate the ability to recover injected planets at 5σ significance with semi-amplitudes down to ≈10 m s−1 with a known ephemeris, more than an order of magnitude below the stellar activity amplitude. However, we find that the accuracy of the recovered semi-amplitudes is ∼50% for such signals with our model.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".